Quantitative Sciences Core

Duke University, Durham NC

Investigators

Linked publications & trials

Abstract

Modified Project Summary/Abstract Section PROJECT SUMMARY – Quantitative Sciences Core The Quantitative Sciences (QS) Core provides expert support to HIV/AIDS investigators at Duke University in data processing, analysis, and interpretation for grant submissions and funded research projects. The QS Core ensures rigor in analysis and provides a wide range of quantitative expertise, including statistical analysis, bioinformatics, computational biology, and epidemiology. We actively promote interdisciplinary team science, and host interdisciplinary colloquia and cross-training seminars such as Immunology for Quants (I4Q) to foster such collaborations. Our approach is structured around specific aims focused on (1) service, (2) education, and (3) innovation. For service, the QS Core faculty and staff assist investigators with grant submissions by providing power calculations for sample size estimation, evaluating alternative designs, and preparing statistical sections for grant applications. This support is particularly valuable for early-stage investigators (ESI) who may struggle to design effective small-scale exploratory studies on a limited budget. The QS Core also collaborates with the Developmental Core to support pilot grant applicants and awardees. Applicants are offered pre-submission consultation to review and critique their experimental design and data analysis plan, and awardees receive continuing statistical and bioinformatics support to ensure their projects’ success. For education, the QS Core provides workshops in biostatistics, data science, machine learning, and assay analyses; provides summer internships for graduate students in quantitative disciplines to work on HIV/AIDS research problems; and trains early career HIV/AIDS researchers in quantitative skills within Duke through our mentored scholars program. For innovation, the QS Core will develop new methods for HIV/AIDS investigators focused on three areas of faculty expertise: pragmatic clinical trials, integration of statistics and machine learning, and extending the Health Atlas for HIV/AIDS research linked to Duke patients and the HIV Samples Biorepository. New to this cycle, we highlight initiatives inspired around (1) Community health – collaborations with the Clinical and SBS Cores and HSR SWG to investigate social drivers of health in PWH; (2) Artificial Intelligence (AI)/Machine Learning (ML) – collaborations with AIT Core to develop ML integrated with statistical modeling for inferential analysis and predictive modeling of complex immunoassays; (3) Human-based research – facilitate the pivoting of HIV/AIDS research via research and education in computational modeling of complex biological systems and pragmatic clinical trials; and (4) development of quantitative online trainings and in-person workshops for HIV analysts. In summary, QS Core faculty and staff provide valuable quantitative expertise paired with HIV domain knowledge and a quantitative expert network, enabling more effective service, training, and innovation for the HIV research community and multidisciplinary research teams.